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Record W4411245844 · doi:10.1177/23996544251351450

Caring beyond mandate: The contribution of community organizations

2025· article· en· W4411245844 on OpenAlexafffundabout
Elizabeth Nelson

Bibliographic record

VenueEnvironment and Planning C Politics and Space · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMandatePolitical scienceSociologyPublic relationsPublic administrationLaw

Abstract

fetched live from OpenAlex

Community organizations perform essential care services that are key to maintaining the well-being and survival of their communities. Often, the care work they undertake benefits underserved urban populations. The labor of these organizations and the support they provide may be underrecognized by municipalities that do not understand their role within the community service landscape, and who do not offer sufficient support for these groups to function securely. The entrenched neoliberal and hegemonic structures characteristic of Canadian municipalities contribute to a structural neglect that places community organizations, and by extension the individuals they serve, in precarity. This hinders the functioning of these collectives and the caring labor they undertake. Drawing on research conducted with community organizations in Cornwall, Kingston, and Ottawa, Ontario, this article highlights the importance of recognizing the care work of community organizations. It posits the benefit that municipal support systems might gain by supporting them in their critical care work to better meet the diverse needs of their communities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.098
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.013
Scholarly communication0.0090.004
Open science0.0010.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.340
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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